As is known in the art, object detection systems for vehicle collision systems are known and used to convey the location of objects that could potentially collide with a vehicle. One previously known way to describe the location of an obstacle is to describe the latitude and longitude of the object. As the number of objects increases, however, the amount of information that must be transmitted to the vehicle also increases. The increase in the amount of transmitted information results in a concomitant increase in the amount of time required by vehicle-mounted systems to process the information. This results in a delay between the receipt of the object location information and a collision warning. This delay reduces valuable response time for a driver of the vehicle and thus makes it more difficult for a driver to take evasive action in order to avoid a collision.
As is also known, for objects moving with rectilinear or curvilinear motion, given a current position, speed and direction of an object, a future position of an object can be accurately predicted relatively easily using well-known kinematic equations of motion.
The motion of some objects, however, is unpredictable. Human beings, for example, do not typically adhere to the basic physics of object motion which can be described by kinematic equations of motion. Rather, human beings in motion are constantly adjusting their speed and direction based upon sensory input. This non-kinematic motion is very difficult (and in some cases, nearly impossible) to express using simple physics equations. Thus, predicting future positions for a pedestrian, for example, can be relatively difficult. In some applications, it is not possible to yield a single position with an acceptable degree of confidence.